https://doi.org/10.1140/epjst/e2014-02145-7
Regular Article
Phase synchronization of instrumental music signals
1 Mathematics Department, Sivanath Sastri College, Kolkata, India
2 Basic Sciences & Humanities Department, Calcutta Institute of Engineering and Management, Kolkata, India
3 Institute for Mathematical Research, Universiti Putra Malaysia, Malaysia
4 Mathematics Department, Faculty of Science, Universiti Putra Malaysia, Malaysia Al-Kindi Cryptography Research Laboratory, Institute for Mathematical Research, Universiti Putra Malaysia, Malaysia
5 Department of Instrumental Music, Rabindra Bharati University, Kolkata-700050, India
Received: 11 March 2014
Revised: 21 March 2014
Published online: 21 April 2014
Signal analysis is one of the finest scientific techniques in communication theory. Some quantitative and qualitative measures describe the pattern of a music signal, vary from one to another. Same musical recital, when played by different instrumentalists, generates different types of music patterns. The reason behind various patterns is the psycho-acoustic measures – Dynamics, Timber, Tonality and Rhythm, varies in each time. However, the psycho-acoustic study of the music signals does not reveal any idea about the similarity between the signals. For such cases, study of synchronization of long-term nonlinear dynamics may provide effective results. In this context, phase synchronization (PS) is one of the measures to show synchronization between two non-identical signals. In fact, it is very critical to investigate any other kind of synchronization for experimental condition, because those are completely non identical signals. Also, there exists equivalence between the phases and the distances of the diagonal line in Recurrence plot (RP) of the signals, which is quantifiable by the recurrence quantification measure τ-recurrence rate. This paper considers two nonlinear music signals based on same raga played by two eminent sitar instrumentalists as two non-identical sources. The psycho-acoustic study shows how the Dynamics, Timber, Tonality and Rhythm vary for the two music signals. Then, long term analysis in the form of phase space reconstruction is performed, which reveals the chaotic phase spaces for both the signals. From the RP of both the phase spaces, τ-recurrence rate is calculated. Finally by the correlation of normalized tau-recurrence rate of their 3D phase spaces and the PS of the two music signals has been established. The numerical results well support the analysis.
© EDP Sciences, Springer-Verlag, 2014